Noonan syndrome (NS) and related disorders are relatively prevalent autosomal dominant traits with features that include short stature, mental retardation and cardiac abnormalities such as pulmonic stenosis and hypertrophic cardiomyopathy (HCM). Mutations altering RAS/mitogen-activated protein kinase components, usually resulting in gain of function, cause these disorders. Roughly 30% of NS remains unexplained by the known genes. Animal model studies reveal that certain aspects of the RASopathies may be treatable, including HCM. SPECIFIC AIM 1 will test the hypothesis that additional genes causing NS will reside outside of the central RAS/MAPK pathway, perhaps altering receptor tyrosine kinase metabolism. To test this hypothesis, we will use a genetically unbiased approach toward gene discovery. Unaffected parent-affected child trios will studied with whole genome sequencing to identify novel NS genes. Targeted resequencing will be used with large cohorts to confirm true positives. In SPECIFIC AIM 2, we hypothesize that candidate therapies for RAF1- related HCM can be identified through screening FDA-approved drugs using a transgenic fruit fly model and that candidate RASopathy therapies identified in fruit flies will prove effective in preventing hypertrophy in mouse models of disease. To test these ideas, we will screen 640 FDA-approved compounds for rescue of pupal lethality in a Raf1 transgenic fly. Hits will be studied for their efficacy curves and for rescue of later developmental phenotypes in several RASopathy fly models. The most promising 10 drugs will then be tested in mice, focusing on HCM in Raf1 mutant mice. Endpoints wil include echocardiographic and histologic parameters. SPECIFIC AIM 3's hypothesis is that efficacious lead compounds for treating RAF1-related HCM can be identified through systems pharmacogenomics. We propose to broaden our efforts by screening a larger library of novel compounds, the Maybridge Hitfinder library of 14,400 compounds, using the same Raf1 fly model. We will employ a multidimensional aproach to prioritizing candidate compounds that uses molecular networks derived from genetic and heart gene expression data from mouse and human populations as well as gene expression signatures from NS mouse models before and after the development of HCM as well as its treatment with a MEK inhibitor. By integrating all available data in a network-based context, we will provide a framework for interpreting our chemical compound candidates. We will then test potential efficacy of 50 prioritized compounds in vitro using cardiomyocytes derived from human induced pluripotent stem cells from a RASopathy patient, using regression of hypertrophy as the endpoint. Taken as a whole, the studies proposed in this application will complete (or nearly complete) the project of identifying the range of genes that cause NS when mutated and significantly advance the identification of novel therapeutics for the RASopathies, focusing on HCM. Successful drugs and compounds would likely be useful for most of the RASopathies and for other important clinical aspects such as developmental delays.